Beyoncé’s album covers in chronological order
Nowadays, Beyoncé is one of my favorite artists. One of the reasons I like to listen to Beyoncé’s music is because she has such a diverse style in her albums. You can find various music genres come back in her music, like R&B, soul, (dance)pop, hiphop, and funk. So far she has produced the following albums, among others:
Because I like Beyoncé’s diversity in styles and genres between and in her albums, I would like to find out with the SpotifyR API features more about Beyoncé’s music and how her music has changed over time. I will do this by analyzing:
I personally notice a number of differences between her albums, for example that her newer albums contain less acoustic songs and that the overall vibe is less positive. Therefore, I’m going to research the acousticness and valence of her albums. I’m expecting them to have shifted downwards after the release of her album Beyoncé, because this album is known for having a different style compared to Beyoncé’s earlier albums. It’s been said a lot that her later albums contained a different, lower end hip hop bass, so I’m curious if this can somehow be seen in this research. In addition, I’m interested in the danceability, energy, and speechiness of her albums. However, I think these features are very high for all her albums, and that no major differences will be seen.
In these graphs, energy, valence, acousticness, and danceability are shown of Beyoncé’s albums.
In these graphs, the speechiness is shown of Beyoncé’s albums. Unfortunately, ggplotly removes the y-axis label, but the label speechiness should be there.
Overall, the speechiness of Beyoncé’s albums is more on the lower side, showing a lot of songs with speechiness-values below 0.1. Songs become non-speech-like with values below 0.33. However, her first two albums seem to have more songs with higher speechiness-values (at least with speechiness-values above 0.2). Still, according to Spotify API, this means that her albums contain mostly non-speech-like songs (songs < 0.33). But since her songs have become more hip hop over the years, I would’ve expected a more clear decreasing shift between the albums.
In this graph, the musical key percentage of Beyoncé’s albums is shown.
After I created this graph, purely out of interest in the keys she uses for her songs, I was not sure if this graph would be of any use for my research. However, the graph does show something I feel is important for my research, namely the diversity in keys she uses in her albums. Besides the fact that the D#/Eb key is neglected in her songs, all the keys are used in songs of at least three of her albums. I’m not sure if this has in any way effect on my opinion that her albums are so diverse, but it shows some contrast between the songs in her albums.
As I already explained in the introduction, I’m interested in the key changes of the song Love On Top, because this song is very well-known for it. Therefore, I will take a look at the chroma and timbre features.In the two self-similarity matrices (SSMs) you can see chroma as well as timbre features of the song Love On Top. Left, you see the chroma features, which show the harmonic and melodic characteristics. On the right, the timbre features are shown, which show the changes in timbre and instrumentation.
In this chromagram, the key changes/modulations of Love On Top (which I explained in the self-similarity matrix) are shown more clearly. As you can see, after 180 seconds the song switches from C major to Db major, D major, Eb major, and lastly to E major.
In this graph, I’ve compared the variables tempo, loudness and duration of two older albums, Dangerously In Love and B-Day Deluxe Edition, with two newer albums, Beyoncé and Lemonade.
The album Beyoncé seems to be different in tempo than the other albums. It’s kind of funny to see that Beyoncé has a lot of songs (seven of the fourteen songs) around a mean tempo of 140 bpm, whereas the songs of the other albums are more spread out.
As we’ve seen in the graph of the preceding page, the album Beyoncé seems to have a different pattern in tempo compared to the albums Dangerously In Love, B-Day Deluxe Edition, and Lemonade. Therefore, I’d like to compare the tempograms of a song from Beyoncé with a song from one of the other three albums.
Heaven has a more ’noisy’tempo. I think this has to do with the acousticness. Since Heaven is almost 100% acoustic and doesn’t have such a stable beat as Hip Hop Star, it could be harder to determine the exact tempo.
In this graph, the difference in timbre coefficients between four of Beyoncé’s albums can be seen.
In this graph, you can see that timbre coefficient c02 stands out as the most important feature. This is remarkable, because c02 has shown to be the most different timbre coefficient between the albums, as you could have seen on the preceding storyboard about timbre coefficients. Maybe this also indicates why this feature is so important in Beyoncé’s music.
Here, Beyoncé’s albums and the accompanying songs are divided in two groups, namely old (her first four albums, untill Beyoncé) and new (her last three albums). The algorithm has made predictions about the distribution of the songs in the two groups based on the feature c02 (since this feature stood out in the graphs of the preceding storyboards).
# A tibble: 2 x 3
class precision recall
<fct> <dbl> <dbl>
1 New 0.571 0.64
2 Old 0.727 0.667
There’s only a small difference between the predictions of the older songs, so this means that timbre coefficient c02 is a big factor in the predictions. Precision and recall are a bit higher compared to the previous model.
# A tibble: 2 x 3
class precision recall
<fct> <dbl> <dbl>
1 New 0.685 0.74
2 Old 0.809 0.764
In this corpus, I’ve analysed four different things, namely: general features of the albums, pitch and timbre features of the song Love On Top, tempo features of Beyoncé’s albums and songs, and timbre features of Beyoncé’s albums. It was very interesting to see the possibilities of Spotify API together with RStudio. So I’ve not only learned a lot about Beyoncé’s music during this course, but also about programming and visualization.
The main things I’ve learned about Beyoncé’s music is that:
It’s impressing how much I’ve learned about Beyoncé’s music only in a few weeks time by Spotify API, and therefore I’m very excited and curious what the future will bring, because I’m sure I’ll use this again for interesting and new musical researches.